On the Integration of Topic Modeling and Dictionary Learning

A new nonparametric Bayesian model is developed to integrate dictionary learning and topic model into a unified framework. The model is employed to analyze partially annotated images, with the dictionary learning performed directly on image patches. Efficient inference is performed with a Gibbsslice sampler, and encouraging results are reported on widely used datasets.

[1]  David B. Dunson,et al.  Dependent Hierarchical Beta Process for Image Interpolation and Denoising , 2011, AISTATS.

[2]  Guillermo Sapiro,et al.  Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations , 2009, NIPS.

[3]  David A. Forsyth,et al.  Matching Words and Pictures , 2003, J. Mach. Learn. Res..

[4]  Michael I. Jordan,et al.  Hierarchical Dirichlet Processes , 2006 .

[5]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[6]  Michael I. Jordan,et al.  Modeling annotated data , 2003, SIGIR.

[7]  J. Sethuraman.  A CONSTRUCTIVE DEFINITION OF DIRICHLET PRIORS , 1991 .

[8]  David B. Dunson,et al.  A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation , 2009, NIPS.

[9]  Thomas L. Griffiths,et al.  Infinite latent feature models and the Indian buffet process , 2005, NIPS.

[10]  David M. Blei,et al.  Supervised Topic Models , 2007, NIPS.

[11]  Pietro Perona,et al.  A Bayesian hierarchical model for learning natural scene categories , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[12]  Yihong Gong,et al.  Linear spatial pyramid matching using sparse coding for image classification , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[13]  Yee Whye Teh,et al.  Stick-breaking Construction for the Indian Buffet Process , 2007, AISTATS.

[14]  Guillermo Sapiro,et al.  Discriminative learned dictionaries for local image analysis , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[15]  Fei-Fei Li,et al.  What, where and who? Classifying events by scene and object recognition , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[16]  Chong Wang,et al.  Simultaneous image classification and annotation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[17]  Michael I. Jordan,et al.  Hierarchical Beta Processes and the Indian Buffet Process , 2007, AISTATS.

[18]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[19]  Li Fei-Fei,et al.  Towards total scene understanding: Classification, annotation and segmentation in an automatic framework , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.